YOLOv10: Real-Time End-to-End Object Detection
Performance
COCO
| Model | Test Size | #Params | FLOPs | AP<sup>val</sup> | Latency |
|---|---|---|---|---|---|
| YOLOv10-N | 640 | 2.3M | 6.7G | 38.5% | 1.84ms |
| YOLOv10-S | 640 | 7.2M | 21.6G | 46.3% | 2.49ms |
| YOLOv10-M | 640 | 15.4M | 59.1G | 51.1% | 4.74ms |
| YOLOv10-B | 640 | 19.1M | 92.0G | 52.5% | 5.74ms |
| YOLOv10-L | 640 | 24.4M | 120.3G | 53.2% | 7.28ms |
| YOLOv10-X | 640 | 29.5M | 160.4G | 54.4% | 10.70ms |
Acknowledgement
The code base is built with ultralytics and RT-DETR.
Thanks for the great implementations!
Citation
If our code or models help your work, please cite our paper:
@article{wang2024yolov10,
title={YOLOv10: Real-Time End-to-End Object Detection},
author={Wang, Ao and Chen, Hui and Liu, Lihao and Chen, Kai and Lin, Zijia and Han, Jungong and Ding, Guiguang},
journal={arXiv preprint arXiv:2405.14458},
year={2024}
}